ks_test.ipynb

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   "source": [
    "from scipy.stats import ks_2samp\n",
    "import numpy as np\n",
    "import random\n",
    "import pandas as pd"
   ]
  },
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   "cell_type": "code",
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     "text": [
      "rand_int1 vs rand_int1 = 1.0\n",
      "rand_int1 vs rand_odd1 = 0.18499855104\n",
      "rand_int1 vs rand_odd2 = 0.454642246381\n",
      "rand_int1 vs rand_even1 = 0.555046581293\n",
      "rand_odd1 vs rand_int1 = 0.18499855104\n",
      "rand_odd1 vs rand_odd1 = 1.0\n",
      "rand_odd1 vs rand_odd2 = 0.117752640131\n",
      "rand_odd1 vs rand_even1 = 0.0376061965701\n",
      "rand_odd2 vs rand_int1 = 0.454642246381\n",
      "rand_odd2 vs rand_odd1 = 0.117752640131\n",
      "rand_odd2 vs rand_odd2 = 1.0\n",
      "rand_odd2 vs rand_even1 = 0.0260394531619\n",
      "rand_even1 vs rand_int1 = 0.555046581293\n",
      "rand_even1 vs rand_odd1 = 0.0376061965701\n",
      "rand_even1 vs rand_odd2 = 0.0260394531619\n",
      "rand_even1 vs rand_even1 = 1.0\n"
     ]
    }
   ],
   "source": [
    "random.seed(3)\n",
    "rand_odd1 = [random.randint(0, 100) * 2 + 1 for x in xrange(10000)]\n",
    "rand_odd2 = [random.randint(0, 100) * 2 + 1 for x in xrange(10000)]\n",
    "rand_even1 = [random.randint(0, 100) * 2 for x in xrange(10000)]\n",
    "rand_int1 = [random.randint(0, 201) for x in xrange(10000)]\n",
    "\n",
    "all_dist = {x:globals()[x] for x in ['rand_odd1', 'rand_odd2', 'rand_even1', 'rand_int1']}\n",
    "print '\\n'.join('%s vs %s = %s' %(k1,k2, ks_2samp(v1,v2).pvalue) for k1,v1 in all_dist.iteritems() \n",
    "                                                                 for k2,v2 in all_dist.iteritems())"
   ]
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